Background and Foreground Subtraction

In this lesson we'll learn:

1. Background Subtraction with Gaussian Mixture-based Background/Foreground Segmentation Algorithm
2. Improved adaptive Gausian mixture model for background subtraction

Taken fron the OpenCV Docs

Background subtraction (BS) is a common and widely used technique for generating a foreground mask (namely, a binary image containing the pixels belonging to moving objects in the scene) by using static cameras.

As the name suggests, BS calculates the foreground mask performing a subtraction between the current frame and a background model, containing the static part of the scene or, more in general, everything that can be considered as background given the characteristics of the observed scene.

Background modeling consists of two main steps:

1. Background Initialization;
2. Background Update.

In the first step, an initial model of the background is computed, while in the second step that model is updated in order to adapt to possible changes in the scene.

Uzbekcha

Fonni ayirish (BS) statik kameralar yordamida oldingi fon niqobini (masalan, sahnadagi harakatlanuvchi ob'ektlarga tegishli piksellarni o'z ichiga olgan ikkilik tasvir) yaratish uchun keng tarqalgan va keng qo'llaniladigan usuldir.

Nomidan ko'rinib turibdiki, BS sahnaning statik qismini yoki umuman olganda, kuzatilayotgan sahnaning xususiyatlarini hisobga olgan holda fon sifatida ko'rib chiqilishi mumkin bo'lgan barcha narsalarni o'z ichiga olgan joriy ramka va fon modeli o'rtasida ayirishni amalga oshiruvchi oldingi fon niqobini hisoblab chiqadi.

Fonni modellashtirish ikki asosiy bosqichdan iborat:

1. Fonni ishga tushirish;
2. Fonni yangilash.

Birinchi bosqichda fonning dastlabki modeli hisoblab chiqiladi, ikkinchi bosqichda esa bu model sahnadagi mumkin bo'lgan o'zgarishlarga moslashish uchun yangilanadi.

What is Background Subtraction?

Background subtraction is a computer vision technique where we seek to isolate the background from the 'moving' foreground. Consider vehciles traversing a roadway, or persons walking along a sidewalk.

It sounds simple in theory (i.e. just keep the station pixels and remove the ones that were changing). However, things like lighting condition changes, shadows etc. can make things get more complicated.

Several algorithms were introduced for this purpose. In the following, we will have a look at two algorithms from the bgsegm module.

Uzbekcha

Fonni ayirma - bu kompyuterni ko'rish usuli bo'lib, biz fonni "harakatlanuvchi" oldingi plandan ajratishga harakat qilamiz. Yo'ldan o'tayotgan transport vositalarini yoki piyodalar yo'lakchasi bo'ylab ketayotgan odamlarni ko'rib chiqing.

Nazariy jihatdan oddiy ko'rinadi (ya'ni, faqat stantsiya piksellarini saqlang va o'zgaruvchanlarini olib tashlang). Biroq, yorug'lik holatining o'zgarishi, soyalar va boshqalar kabi narsalarni murakkablashtirishi mumkin.

Shu maqsadda bir nechta algoritmlar kiritilgan. Quyida biz bgsegm modulidan ikkita algoritmni ko'rib chiqamiz.

import cv2
import numpy as np
from matplotlib import pyplot as plt

# Define our imshow function 
def imshow(title = "Image", image = None, size = 10):
    w, h = image.shape[0], image.shape[1]
    aspect_ratio = w/h
    plt.figure(figsize=(size * aspect_ratio,size))
    plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
    plt.title(title)
    plt.show()

1-usul. Gaussian Mixture-based Background/Foreground Segmentation Algorithm

In this paper, we propose a background subtraction (BGS) method based on the Gaussian mixture models using color and depth information. For combining color and depth information, we used the probabilistic model based on Gaussian distribution. In particular, we focused on solving color camouflage problem and depth denoising. For evaluating our method, we built a new dataset containing normal, color camouflage and depth camouflage situations. The dataset files consist of color, depth and ground truth image sequences. With these files, we compared the proposed algorithm with the conventional color-based BGS techniques in terms of precision, recall and F-measure. As a result, our method showed the best performance. Thus, this technique will help to robustly detect regions of interest as pre-processing in high-level image processing stages.

Link to Paper - https://www.researchgate.net/publication/283026260_Background_subtraction_based_on_Gaussian_mixture_models_using_color_and_depth_information

Uzbekcha

Ushbu maqolada biz rang va chuqurlik ma'lumotlaridan foydalangan holda Gauss aralashmasi modellariga asoslangan fonni olib tashlash (BGS) usulini taklif qilamiz. Rang va chuqurlik ma'lumotlarini birlashtirish uchun biz Gauss taqsimotiga asoslangan ehtimollik modelidan foydalandik. Xususan, biz ranglarni kamuflyaj muammosini va chuqurlikni yo'qotish muammosini hal qilishga e'tibor qaratdik. Bizning usulimizni baholash uchun biz oddiy, rangli kamuflyaj va chuqurlikdagi kamuflyaj holatlarini o'z ichiga olgan yangi ma'lumotlar to'plamini yaratdik. Ma'lumotlar to'plami fayllari rang, chuqurlik va asosiy haqiqat tasvirlari ketma-ketliklaridan iborat. Ushbu fayllar yordamida biz taklif qilingan algoritmni an'anaviy rangga asoslangan BGS texnikasi bilan aniqlik, eslab qolish va F o'lchovi nuqtai nazaridan solishtirdik. Natijada, bizning usulimiz eng yaxshi ko'rsatkichni ko'rsatdi. Shunday qilib, ushbu uslub yuqori darajadagi tasvirni qayta ishlash bosqichlarida oldindan ishlov berish sifatida qiziqish hududlarini ishonchli aniqlashga yordam beradi.

cap = cv2.VideoCapture('Datasets/videos/walking.mp4')

w = int(cap.get(3)) #3 frame eni olchami
h = int(cap.get(4)) #4 parametr frame boyi olchami 

fourcc = cv2.VideoWriter_fourcc(*'MPV4')
#out = cv2.VideoWriter('Datasets/videos/walking_GaussianM.mp4', fourcc, 30, (w, h))#here 3-frame

#initialize background subtraction 
bsMOG = cv2.bgsegm.createBackgroundSubtractorMOG()

while cap.isOpened(): 
    
    ret, frame = cap.read()
    
    if ret:
        #bse ni apply methodidan foydalanib foreground maskni olamiz. 
        foreground_mask = bsMOG.apply(frame)
        #out.write(foreground_mask) #ajralgan foregroundni yozib ko'ramiz. 
        imshow('Foreground mask', foreground_mask)

        #cv2.imshow('foreground_mask', foreground_mask)
        if cv2.waitKey(1) & 0xFF==ord('q'):
            break
    else:
        break

cap.release()
#out.release()
cv2.destroyAllWindows()

---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
Input In [6], in <cell line: 12>()
     14 ret, frame = cap.read()
     16 if ret:
     17     #bse ni apply methodidan foydalanib foreground maskni olamiz. 
---> 18     foreground_mask = bsMOG.apply(frame)
     19     #out.write(foreground_mask) #ajralgan foregroundni yozib ko'ramiz. 
     20     imshow('Foreground mask', foreground_mask)

KeyboardInterrupt: 

2-usul. Improved adaptive Gausian mixture model for background subtraction

Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient adaptive algorithm using Gaussian mixture probability density. Recursive equations are used to constantly update the parameters and but also to simultaneously select the appropriate number of components for each pixel.

https://www.researchgate.net/publication/4090386_Improved_Adaptive_Gaussian_Mixture_Model_for_Background_Subtraction

Orqa fonni olib tashlash - bu kompyuterni ko'rishning keng tarqalgan vazifasi. Biz odatdagi piksel darajasidagi yondashuvni tahlil qilamiz. Biz Gauss aralashmasi ehtimoli zichligidan foydalangan holda samarali adaptiv algoritmni ishlab chiqamiz. Rekursiv tenglamalar parametrlarni doimiy ravishda yangilash uchun, shuningdek, bir vaqtning o'zida har bir piksel uchun mos keladigan komponentlar sonini tanlash uchun ishlatiladi.

cap = cv2.VideoCapture('Datasets/videos/walking.mp4')

w = int(cap.get(3)) #3 frame eni olchami
h = int(cap.get(4)) #4 parametr frame boyi olchami 
fps = int(cap.get(5)) #5 parametr fps 
print('Frames per second : ', fps,'FPS')
frame_count = cap.get(7)
print('Frame count : ', frame_count)

fourcc = cv2.VideoWriter_fourcc(*'MPV4')
out = cv2.VideoWriter('Datasets/videos/walking_AdaptiveGM.mp4', fourcc, 30, (w, h))

# Initlaize background subtractor
bsGSOC = cv2.bgsegm.createBackgroundSubtractorGSOC()

# Loop once video is successfully loaded
while True:
    ret, frame = cap.read()
    if ret: 
        #bs ni apply methodidan foydalanib foreground maskni olamiz. 
        foreground_mask = bsGSOC.apply(frame)
        #out.write(foreground_mask)
        #imshow("Foreground Mask", foreground_mask)
        
        cv2.imshow('foreground_mask', foreground_mask)
        if cv2.waitKey(1) & 0xFF==ord('q'):
            break
    else:
        break

        
cap.release()
out.release()
cv2.destroyAllWindows()

Frames per second :  30 FPS
Frame count :  461.0

---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
Input In [2], in <cell line: 17>()
     22 foreground_mask = bsGSOC.apply(frame)
     23 #out.write(foreground_mask)
     24 #
---> 25 imshow("Foreground Mask", foreground_mask)
     27 res = cv2.bitwise_and(gray, foreground_mask) 
     28 cv2.imshow('foreground_mask', res)

Input In [1], in imshow(title, image, size)
     10 plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
     11 plt.title(title)
---> 12 plt.show()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\pyplot.py:368, in show(*args, **kwargs)
    324 """
    325 Display all open figures.
    326 
   (...)
    365 explicitly there.
    366 """
    367 _warn_if_gui_out_of_main_thread()
--> 368 return _backend_mod.show(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib_inline\backend_inline.py:41, in show(close, block)
     39 try:
     40     for figure_manager in Gcf.get_all_fig_managers():
---> 41         display(
     42             figure_manager.canvas.figure,
     43             metadata=_fetch_figure_metadata(figure_manager.canvas.figure)
     44         )
     45 finally:
     46     show._to_draw = []

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\display_functions.py:298, in display(include, exclude, metadata, transient, display_id, raw, clear, *objs, **kwargs)
    296     publish_display_data(data=obj, metadata=metadata, **kwargs)
    297 else:
--> 298     format_dict, md_dict = format(obj, include=include, exclude=exclude)
    299     if not format_dict:
    300         # nothing to display (e.g. _ipython_display_ took over)
    301         continue

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:178, in DisplayFormatter.format(self, obj, include, exclude)
    176 md = None
    177 try:
--> 178     data = formatter(obj)
    179 except:
    180     # FIXME: log the exception
    181     raise

File ~\anaconda3\envs\data_science\lib\site-packages\decorator.py:232, in decorate.<locals>.fun(*args, **kw)
    230 if not kwsyntax:
    231     args, kw = fix(args, kw, sig)
--> 232 return caller(func, *(extras + args), **kw)

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:222, in catch_format_error(method, self, *args, **kwargs)
    220 """show traceback on failed format call"""
    221 try:
--> 222     r = method(self, *args, **kwargs)
    223 except NotImplementedError:
    224     # don't warn on NotImplementedErrors
    225     return self._check_return(None, args[0])

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:339, in BaseFormatter.__call__(self, obj)
    337     pass
    338 else:
--> 339     return printer(obj)
    340 # Finally look for special method names
    341 method = get_real_method(obj, self.print_method)

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\pylabtools.py:151, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    148     from matplotlib.backend_bases import FigureCanvasBase
    149     FigureCanvasBase(fig)
--> 151 fig.canvas.print_figure(bytes_io, **kw)
    152 data = bytes_io.getvalue()
    153 if fmt == 'svg':

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\backend_bases.py:2295, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2289     renderer = _get_renderer(
   2290         self.figure,
   2291         functools.partial(
   2292             print_method, orientation=orientation)
   2293     )
   2294     with getattr(renderer, "_draw_disabled", nullcontext)():
-> 2295         self.figure.draw(renderer)
   2297 if bbox_inches:
   2298     if bbox_inches == "tight":

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:73, in _finalize_rasterization.<locals>.draw_wrapper(artist, renderer, *args, **kwargs)
     71 @wraps(draw)
     72 def draw_wrapper(artist, renderer, *args, **kwargs):
---> 73     result = draw(artist, renderer, *args, **kwargs)
     74     if renderer._rasterizing:
     75         renderer.stop_rasterizing()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\figure.py:2810, in Figure.draw(self, renderer)
   2807         # ValueError can occur when resizing a window.
   2809 self.patch.draw(renderer)
-> 2810 mimage._draw_list_compositing_images(
   2811     renderer, self, artists, self.suppressComposite)
   2813 for sfig in self.subfigs:
   2814     sfig.draw(renderer)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\image.py:132, in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    130 if not_composite or not has_images:
    131     for a in artists:
--> 132         a.draw(renderer)
    133 else:
    134     # Composite any adjacent images together
    135     image_group = []

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_base.py:3046, in _AxesBase.draw(self, renderer)
   3043     for spine in self.spines.values():
   3044         artists.remove(spine)
-> 3046 self._update_title_position(renderer)
   3048 if not self.axison:
   3049     for _axis in self._get_axis_list():

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_base.py:2996, in _AxesBase._update_title_position(self, renderer)
   2994     _log.debug('top of Axes not in the figure, so title not moved')
   2995     return
-> 2996 if title.get_window_extent(renderer).ymin < top:
   2997     _, y = self.transAxes.inverted().transform((0, top))
   2998     title.set_position((x, y))

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\text.py:910, in Text.get_window_extent(self, renderer, dpi)
    907     raise RuntimeError('Cannot get window extent w/o renderer')
    909 with cbook._setattr_cm(self.figure, dpi=dpi):
--> 910     bbox, info, descent = self._get_layout(self._renderer)
    911     x, y = self.get_unitless_position()
    912     x, y = self.get_transform().transform((x, y))

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\text.py:309, in Text._get_layout(self, renderer)
    306 ys = []
    308 # Full vertical extent of font, including ascenders and descenders:
--> 309 _, lp_h, lp_d = renderer.get_text_width_height_descent(
    310     "lp", self._fontproperties,
    311     ismath="TeX" if self.get_usetex() else False)
    312 min_dy = (lp_h - lp_d) * self._linespacing
    314 for i, line in enumerate(lines):

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\backends\backend_agg.py:270, in RendererAgg.get_text_width_height_descent(self, s, prop, ismath)
    268 flags = get_hinting_flag()
    269 font = self._get_agg_font(prop)
--> 270 font.set_text(s, 0.0, flags=flags)
    271 w, h = font.get_width_height()  # width and height of unrotated string
    272 d = font.get_descent()

KeyboardInterrupt: 

Bitwise yordamida foregroundni yaxshiroq korish

cap = cv2.VideoCapture('Datasets/videos/walking.mp4')


# Initlaize background subtractor
bsGSOC = cv2.bgsegm.createBackgroundSubtractorGSOC()

# Loop once video is successfully loaded
while True:
    ret, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    if ret: 
        #bs ni apply methodidan foydalanib foreground maskni olamiz. 
        foreground_mask = bsGSOC.apply(frame)
        res = cv2.bitwise_and(gray, foreground_mask) 
        
        imshow("Foreground Mask", res)
        
    else:
        break

        
cap.release()
cv2.destroyAllWindows()

---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
Input In [3], in <cell line: 8>()
     13     foreground_mask = bsGSOC.apply(frame)
     14     res = cv2.bitwise_and(gray, foreground_mask) 
---> 16     imshow("Foreground Mask", res)
     18 else:
     19     break

Input In [2], in imshow(title, image, size)
     10 plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
     11 plt.title(title)
---> 12 plt.show()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\pyplot.py:368, in show(*args, **kwargs)
    324 """
    325 Display all open figures.
    326 
   (...)
    365 explicitly there.
    366 """
    367 _warn_if_gui_out_of_main_thread()
--> 368 return _backend_mod.show(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib_inline\backend_inline.py:41, in show(close, block)
     39 try:
     40     for figure_manager in Gcf.get_all_fig_managers():
---> 41         display(
     42             figure_manager.canvas.figure,
     43             metadata=_fetch_figure_metadata(figure_manager.canvas.figure)
     44         )
     45 finally:
     46     show._to_draw = []

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\display_functions.py:298, in display(include, exclude, metadata, transient, display_id, raw, clear, *objs, **kwargs)
    296     publish_display_data(data=obj, metadata=metadata, **kwargs)
    297 else:
--> 298     format_dict, md_dict = format(obj, include=include, exclude=exclude)
    299     if not format_dict:
    300         # nothing to display (e.g. _ipython_display_ took over)
    301         continue

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:178, in DisplayFormatter.format(self, obj, include, exclude)
    176 md = None
    177 try:
--> 178     data = formatter(obj)
    179 except:
    180     # FIXME: log the exception
    181     raise

File ~\anaconda3\envs\data_science\lib\site-packages\decorator.py:232, in decorate.<locals>.fun(*args, **kw)
    230 if not kwsyntax:
    231     args, kw = fix(args, kw, sig)
--> 232 return caller(func, *(extras + args), **kw)

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:222, in catch_format_error(method, self, *args, **kwargs)
    220 """show traceback on failed format call"""
    221 try:
--> 222     r = method(self, *args, **kwargs)
    223 except NotImplementedError:
    224     # don't warn on NotImplementedErrors
    225     return self._check_return(None, args[0])

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:339, in BaseFormatter.__call__(self, obj)
    337     pass
    338 else:
--> 339     return printer(obj)
    340 # Finally look for special method names
    341 method = get_real_method(obj, self.print_method)

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\pylabtools.py:151, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    148     from matplotlib.backend_bases import FigureCanvasBase
    149     FigureCanvasBase(fig)
--> 151 fig.canvas.print_figure(bytes_io, **kw)
    152 data = bytes_io.getvalue()
    153 if fmt == 'svg':

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\backend_bases.py:2299, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2297 if bbox_inches:
   2298     if bbox_inches == "tight":
-> 2299         bbox_inches = self.figure.get_tightbbox(
   2300             renderer, bbox_extra_artists=bbox_extra_artists)
   2301         if pad_inches is None:
   2302             pad_inches = rcParams['savefig.pad_inches']

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\figure.py:1641, in FigureBase.get_tightbbox(self, renderer, bbox_extra_artists)
   1637 if ax.get_visible():
   1638     # some axes don't take the bbox_extra_artists kwarg so we
   1639     # need this conditional....
   1640     try:
-> 1641         bbox = ax.get_tightbbox(
   1642             renderer, bbox_extra_artists=bbox_extra_artists)
   1643     except TypeError:
   1644         bbox = ax.get_tightbbox(renderer)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_base.py:4619, in _AxesBase.get_tightbbox(self, renderer, call_axes_locator, bbox_extra_artists, for_layout_only)
   4617 if self.xaxis.get_visible():
   4618     try:
-> 4619         bb_xaxis = self.xaxis.get_tightbbox(
   4620             renderer, for_layout_only=for_layout_only)
   4621     except TypeError:
   4622         # in case downstream library has redefined axis:
   4623         bb_xaxis = self.xaxis.get_tightbbox(renderer)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:1108, in Axis.get_tightbbox(self, renderer, for_layout_only)
   1105 self._update_label_position(renderer)
   1107 # go back to just this axis's tick labels
-> 1108 ticklabelBoxes, ticklabelBoxes2 = self._get_tick_bboxes(
   1109             ticks_to_draw, renderer)
   1111 self._update_offset_text_position(ticklabelBoxes, ticklabelBoxes2)
   1112 self.offsetText.set_text(self.major.formatter.get_offset())

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:1085, in Axis._get_tick_bboxes(self, ticks, renderer)
   1083 def _get_tick_bboxes(self, ticks, renderer):
   1084     """Return lists of bboxes for ticks' label1's and label2's."""
-> 1085     return ([tick.label1.get_window_extent(renderer)
   1086              for tick in ticks if tick.label1.get_visible()],
   1087             [tick.label2.get_window_extent(renderer)
   1088              for tick in ticks if tick.label2.get_visible()])

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:1085, in <listcomp>(.0)
   1083 def _get_tick_bboxes(self, ticks, renderer):
   1084     """Return lists of bboxes for ticks' label1's and label2's."""
-> 1085     return ([tick.label1.get_window_extent(renderer)
   1086              for tick in ticks if tick.label1.get_visible()],
   1087             [tick.label2.get_window_extent(renderer)
   1088              for tick in ticks if tick.label2.get_visible()])

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\text.py:912, in Text.get_window_extent(self, renderer, dpi)
    910 bbox, info, descent = self._get_layout(self._renderer)
    911 x, y = self.get_unitless_position()
--> 912 x, y = self.get_transform().transform((x, y))
    913 bbox = bbox.translated(x, y)
    914 return bbox

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\transforms.py:1503, in Transform.transform(self, values)
   1500 values = values.reshape((-1, self.input_dims))
   1502 # Transform the values
-> 1503 res = self.transform_affine(self.transform_non_affine(values))
   1505 # Convert the result back to the shape of the input values.
   1506 if ndim == 0:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\transforms.py:2419, in CompositeGenericTransform.transform_affine(self, points)
   2417 def transform_affine(self, points):
   2418     # docstring inherited
-> 2419     return self.get_affine().transform(points)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\transforms.py:2446, in CompositeGenericTransform.get_affine(self)
   2444     return self._b.get_affine()
   2445 else:
-> 2446     return Affine2D(np.dot(self._b.get_affine().get_matrix(),
   2447                            self._a.get_affine().get_matrix()))

File <__array_function__ internals>:180, in dot(*args, **kwargs)

KeyboardInterrupt: 

3-usul. Background Substraction KKN

The parameters if you wish to veer away from the default settings:

• history is the number of frames used to build the statistic model of the background. The smaller the value is, the faster changes in the background will be taken into account by the model and thus be considered as background. And vice versa.
• dist2Threshold is a threshold to define whether a pixel is different from the background or not. The smaller the value is, the more sensitive movement detection is. And vice versa.
• detectShadows : If set to true, shadows will be displayed in gray on the generated mask. (Example bellow)

https://docs.opencv.org/master/de/de1/group__video__motion.html#gac9be925771f805b6fdb614ec2292006d

cap = cv2.VideoCapture('Datasets/videos/walking.mp4')

# Get the height and width of the frame (required to be an interfer)
w = int(cap.get(3))
h = int(cap.get(4))

# Define the codec and create VideoWriter object.The output is stored in 'outpy.avi' file.
out = cv2.VideoWriter('Datasets/videos/output/walking_Bsubtraction_KNN.mp4', cv2.VideoWriter_fourcc(*'MPV4'), 30, (w, h))

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(3,3))
bsKNN = cv2.createBackgroundSubtractorKNN()

while(1):
    ret, frame = cap.read()

    if ret:
        fgmask = bsKNN.apply(frame)
        fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel) #denoising qilish uchun qollandi

        imshow('frame', fgmask)
#         cv2.imshow('Background substruction KNN', fgmask)
        
#         if cv2.waitKey(1) & 0xFF==ord('q'):
#             break
    
    else:
        break

cap.release()
out.release()

---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
Input In [2], in <cell line: 13>()
     17         fgmask = bsKNN.apply(frame)
     18         fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel) #denoising qilish uchun qollandi
---> 20         imshow('frame', fgmask)
     21 #         cv2.imshow('Background substruction KNN', fgmask)
     22         
     23 #         if cv2.waitKey(1) & 0xFF==ord('q'):
     24 #             break
     25     
     26     else:
     27         break

Input In [1], in imshow(title, image, size)
     10 plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
     11 plt.title(title)
---> 12 plt.show()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\pyplot.py:368, in show(*args, **kwargs)
    324 """
    325 Display all open figures.
    326 
   (...)
    365 explicitly there.
    366 """
    367 _warn_if_gui_out_of_main_thread()
--> 368 return _backend_mod.show(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib_inline\backend_inline.py:41, in show(close, block)
     39 try:
     40     for figure_manager in Gcf.get_all_fig_managers():
---> 41         display(
     42             figure_manager.canvas.figure,
     43             metadata=_fetch_figure_metadata(figure_manager.canvas.figure)
     44         )
     45 finally:
     46     show._to_draw = []

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\display_functions.py:298, in display(include, exclude, metadata, transient, display_id, raw, clear, *objs, **kwargs)
    296     publish_display_data(data=obj, metadata=metadata, **kwargs)
    297 else:
--> 298     format_dict, md_dict = format(obj, include=include, exclude=exclude)
    299     if not format_dict:
    300         # nothing to display (e.g. _ipython_display_ took over)
    301         continue

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:178, in DisplayFormatter.format(self, obj, include, exclude)
    176 md = None
    177 try:
--> 178     data = formatter(obj)
    179 except:
    180     # FIXME: log the exception
    181     raise

File ~\anaconda3\envs\data_science\lib\site-packages\decorator.py:232, in decorate.<locals>.fun(*args, **kw)
    230 if not kwsyntax:
    231     args, kw = fix(args, kw, sig)
--> 232 return caller(func, *(extras + args), **kw)

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:222, in catch_format_error(method, self, *args, **kwargs)
    220 """show traceback on failed format call"""
    221 try:
--> 222     r = method(self, *args, **kwargs)
    223 except NotImplementedError:
    224     # don't warn on NotImplementedErrors
    225     return self._check_return(None, args[0])

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\formatters.py:339, in BaseFormatter.__call__(self, obj)
    337     pass
    338 else:
--> 339     return printer(obj)
    340 # Finally look for special method names
    341 method = get_real_method(obj, self.print_method)

File ~\anaconda3\envs\data_science\lib\site-packages\IPython\core\pylabtools.py:151, in print_figure(fig, fmt, bbox_inches, base64, **kwargs)
    148     from matplotlib.backend_bases import FigureCanvasBase
    149     FigureCanvasBase(fig)
--> 151 fig.canvas.print_figure(bytes_io, **kw)
    152 data = bytes_io.getvalue()
    153 if fmt == 'svg':

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\backend_bases.py:2319, in FigureCanvasBase.print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)
   2315 try:
   2316     # _get_renderer may change the figure dpi (as vector formats
   2317     # force the figure dpi to 72), so we need to set it again here.
   2318     with cbook._setattr_cm(self.figure, dpi=dpi):
-> 2319         result = print_method(
   2320             filename,
   2321             facecolor=facecolor,
   2322             edgecolor=edgecolor,
   2323             orientation=orientation,
   2324             bbox_inches_restore=_bbox_inches_restore,
   2325             **kwargs)
   2326 finally:
   2327     if bbox_inches and restore_bbox:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\backend_bases.py:1648, in _check_savefig_extra_args.<locals>.wrapper(*args, **kwargs)
   1640     _api.warn_deprecated(
   1641         '3.3', name=name, removal='3.6',
   1642         message='%(name)s() got unexpected keyword argument "'
   1643                 + arg + '" which is no longer supported as of '
   1644                 '%(since)s and will become an error '
   1645                 '%(removal)s')
   1646     kwargs.pop(arg)
-> 1648 return func(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\_api\deprecation.py:412, in delete_parameter.<locals>.wrapper(*inner_args, **inner_kwargs)
    402     deprecation_addendum = (
    403         f"If any parameter follows {name!r}, they should be passed as "
    404         f"keyword, not positionally.")
    405     warn_deprecated(
    406         since,
    407         name=repr(name),
   (...)
    410                  else deprecation_addendum,
    411         **kwargs)
--> 412 return func(*inner_args, **inner_kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\backends\backend_agg.py:540, in FigureCanvasAgg.print_png(self, filename_or_obj, metadata, pil_kwargs, *args)
    490 @_check_savefig_extra_args
    491 @_api.delete_parameter("3.5", "args")
    492 def print_png(self, filename_or_obj, *args,
    493               metadata=None, pil_kwargs=None):
    494     """
    495     Write the figure to a PNG file.
    496 
   (...)
    538         *metadata*, including the default 'Software' key.
    539     """
--> 540     FigureCanvasAgg.draw(self)
    541     mpl.image.imsave(
    542         filename_or_obj, self.buffer_rgba(), format="png", origin="upper",
    543         dpi=self.figure.dpi, metadata=metadata, pil_kwargs=pil_kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\backends\backend_agg.py:436, in FigureCanvasAgg.draw(self)
    432 # Acquire a lock on the shared font cache.
    433 with RendererAgg.lock, \
    434      (self.toolbar._wait_cursor_for_draw_cm() if self.toolbar
    435       else nullcontext()):
--> 436     self.figure.draw(self.renderer)
    437     # A GUI class may be need to update a window using this draw, so
    438     # don't forget to call the superclass.
    439     super().draw()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:73, in _finalize_rasterization.<locals>.draw_wrapper(artist, renderer, *args, **kwargs)
     71 @wraps(draw)
     72 def draw_wrapper(artist, renderer, *args, **kwargs):
---> 73     result = draw(artist, renderer, *args, **kwargs)
     74     if renderer._rasterizing:
     75         renderer.stop_rasterizing()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\figure.py:2810, in Figure.draw(self, renderer)
   2807         # ValueError can occur when resizing a window.
   2809 self.patch.draw(renderer)
-> 2810 mimage._draw_list_compositing_images(
   2811     renderer, self, artists, self.suppressComposite)
   2813 for sfig in self.subfigs:
   2814     sfig.draw(renderer)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\image.py:132, in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    130 if not_composite or not has_images:
    131     for a in artists:
--> 132         a.draw(renderer)
    133 else:
    134     # Composite any adjacent images together
    135     image_group = []

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_base.py:3082, in _AxesBase.draw(self, renderer)
   3079         a.draw(renderer)
   3080     renderer.stop_rasterizing()
-> 3082 mimage._draw_list_compositing_images(
   3083     renderer, self, artists, self.figure.suppressComposite)
   3085 renderer.close_group('axes')
   3086 self.stale = False

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\image.py:132, in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
    130 if not_composite or not has_images:
    131     for a in artists:
--> 132         a.draw(renderer)
    133 else:
    134     # Composite any adjacent images together
    135     image_group = []

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:50, in allow_rasterization.<locals>.draw_wrapper(artist, renderer)
     47     if artist.get_agg_filter() is not None:
     48         renderer.start_filter()
---> 50     return draw(artist, renderer)
     51 finally:
     52     if artist.get_agg_filter() is not None:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\image.py:646, in _ImageBase.draw(self, renderer, *args, **kwargs)
    644         renderer.draw_image(gc, l, b, im, trans)
    645 else:
--> 646     im, l, b, trans = self.make_image(
    647         renderer, renderer.get_image_magnification())
    648     if im is not None:
    649         renderer.draw_image(gc, l, b, im)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\image.py:956, in AxesImage.make_image(self, renderer, magnification, unsampled)
    953 transformed_bbox = TransformedBbox(bbox, trans)
    954 clip = ((self.get_clip_box() or self.axes.bbox) if self.get_clip_on()
    955         else self.figure.bbox)
--> 956 return self._make_image(self._A, bbox, transformed_bbox, clip,
    957                         magnification, unsampled=unsampled)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\image.py:557, in _ImageBase._make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification, unsampled, round_to_pixel_border)
    554     alpha = self._get_scalar_alpha()
    555     output_alpha = _resample(  # resample alpha channel
    556         self, A[..., 3], out_shape, t, alpha=alpha)
--> 557     output = _resample(  # resample rgb channels
    558         self, _rgb_to_rgba(A[..., :3]), out_shape, t, alpha=alpha)
    559     output[..., 3] = output_alpha  # recombine rgb and alpha
    561 # at this point output is either a 2D array of normed data
    562 # (of int or float)
    563 # or an RGBA array of re-sampled input

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\image.py:193, in _resample(image_obj, data, out_shape, transform, resample, alpha)
    191 if resample is None:
    192     resample = image_obj.get_resample()
--> 193 _image.resample(data, out, transform,
    194                 _interpd_[interpolation],
    195                 resample,
    196                 alpha,
    197                 image_obj.get_filternorm(),
    198                 image_obj.get_filterrad())
    199 return out

KeyboardInterrupt: 

Foreground Subtraction

cap = cv2.VideoCapture('Datasets/videos/walking.mp4')

# Get the height and width of the frame (required to be an interfer)
w = int(cap.get(3))
h = int(cap.get(4))

# Define the codec and create VideoWriter object.The output is stored in 'outpy.avi' file.
out = cv2.VideoWriter('Datasets/videos/output/walking_foreground.mp4', cv2.VideoWriter_fourcc(*'MPV4'), 30, (w, h))
ret, frame = cap.read()

# Create a flaot numpy array with frame values
average = np.float32(frame)

while True:

    ret, frame = cap.read()

    if ret: 
      
        # 0.01 is the weight of image, play around to see how it changes
        cv2.accumulateWeighted(frame, average, 0.01)

        # Scales, calculates absolute values, and converts the result to 8-bit
        background = cv2.convertScaleAbs(average)

        imshow('Input', frame)
        imshow('Disapearing Background', background)
        out.write(background)
#         cv2.imshow("original", frame)
#         cv2.imshow('Disapearing Background', background)
#         if cv2.waitKey(1) & 0xFF==ord('q'):
#             break
        

    else:
          break

cap.release()
out.release()
cv2.destroyAllWindows()

---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
Input In [15], in <cell line: 14>()
     24         background = cv2.convertScaleAbs(average)
     26         imshow('Input', frame)
---> 27         imshow('Disapearing Background', background)
     28         out.write(background)
     29 #         cv2.imshow("original", frame)
     30 #         cv2.imshow('Disapearing Background', background)
     31 #         if cv2.waitKey(1) & 0xFF==ord('q'):
   (...)
     34 
     35     else:

Input In [2], in imshow(title, image, size)
      8 aspect_ratio = w/h
      9 plt.figure(figsize=(size * aspect_ratio,size))
---> 10 plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
     11 plt.title(title)
     12 plt.show()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\_api\deprecation.py:456, in make_keyword_only.<locals>.wrapper(*args, **kwargs)
    450 if len(args) > name_idx:
    451     warn_deprecated(
    452         since, message="Passing the %(name)s %(obj_type)s "
    453         "positionally is deprecated since Matplotlib %(since)s; the "
    454         "parameter will become keyword-only %(removal)s.",
    455         name=name, obj_type=f"parameter of {func.__name__}()")
--> 456 return func(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\pyplot.py:2640, in imshow(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, interpolation_stage, filternorm, filterrad, resample, url, data, **kwargs)
   2634 @_copy_docstring_and_deprecators(Axes.imshow)
   2635 def imshow(
   2636         X, cmap=None, norm=None, aspect=None, interpolation=None,
   2637         alpha=None, vmin=None, vmax=None, origin=None, extent=None, *,
   2638         interpolation_stage=None, filternorm=True, filterrad=4.0,
   2639         resample=None, url=None, data=None, **kwargs):
-> 2640     __ret = gca().imshow(
   2641         X, cmap=cmap, norm=norm, aspect=aspect,
   2642         interpolation=interpolation, alpha=alpha, vmin=vmin,
   2643         vmax=vmax, origin=origin, extent=extent,
   2644         interpolation_stage=interpolation_stage,
   2645         filternorm=filternorm, filterrad=filterrad, resample=resample,
   2646         url=url, **({"data": data} if data is not None else {}),
   2647         **kwargs)
   2648     sci(__ret)
   2649     return __ret

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\pyplot.py:2262, in gca(**kwargs)
   2260 @_copy_docstring_and_deprecators(Figure.gca)
   2261 def gca(**kwargs):
-> 2262     return gcf().gca(**kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\figure.py:1515, in FigureBase.gca(self, **kwargs)
   1505     _api.warn_deprecated(
   1506         "3.4",
   1507         message="Calling gca() with keyword arguments was deprecated "
   (...)
   1512         "axes with non-default arguments, use plt.axes() or "
   1513         "plt.subplot().")
   1514 if self._axstack.empty():
-> 1515     return self.add_subplot(1, 1, 1, **kwargs)
   1516 else:
   1517     return self._axstack()

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\figure.py:772, in FigureBase.add_subplot(self, *args, **kwargs)
    769         args = tuple(map(int, str(args[0])))
    770     projection_class, pkw = self._process_projection_requirements(
    771         *args, **kwargs)
--> 772     ax = subplot_class_factory(projection_class)(self, *args, **pkw)
    773     key = (projection_class, pkw)
    774 return self._add_axes_internal(ax, key)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_subplots.py:34, in SubplotBase.__init__(self, fig, *args, **kwargs)
     15 """
     16 Parameters
     17 ----------
   (...)
     31     Keyword arguments are passed to the Axes (sub)class constructor.
     32 """
     33 # _axes_class is set in the subplot_class_factory
---> 34 self._axes_class.__init__(self, fig, [0, 0, 1, 1], **kwargs)
     35 # This will also update the axes position.
     36 self.set_subplotspec(SubplotSpec._from_subplot_args(fig, args))

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\_api\deprecation.py:456, in make_keyword_only.<locals>.wrapper(*args, **kwargs)
    450 if len(args) > name_idx:
    451     warn_deprecated(
    452         since, message="Passing the %(name)s %(obj_type)s "
    453         "positionally is deprecated since Matplotlib %(since)s; the "
    454         "parameter will become keyword-only %(removal)s.",
    455         name=name, obj_type=f"parameter of {func.__name__}()")
--> 456 return func(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_base.py:632, in _AxesBase.__init__(self, fig, rect, facecolor, frameon, sharex, sharey, label, xscale, yscale, box_aspect, **kwargs)
    629 self.set_axisbelow(mpl.rcParams['axes.axisbelow'])
    631 self._rasterization_zorder = None
--> 632 self.cla()
    634 # funcs used to format x and y - fall back on major formatters
    635 self.fmt_xdata = None

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_base.py:1249, in _AxesBase.cla(self)
   1246 self.legend_ = None
   1247 self.containers = []
-> 1249 self.grid(False)  # Disable grid on init to use rcParameter
   1250 self.grid(self._gridOn, which=mpl.rcParams['axes.grid.which'],
   1251           axis=mpl.rcParams['axes.grid.axis'])
   1252 props = font_manager.FontProperties(
   1253     size=mpl.rcParams['axes.titlesize'],
   1254     weight=mpl.rcParams['axes.titleweight'])

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\_api\deprecation.py:299, in rename_parameter.<locals>.wrapper(*args, **kwargs)
    294     warn_deprecated(
    295         since, message=f"The {old!r} parameter of {func.__name__}() "
    296         f"has been renamed {new!r} since Matplotlib {since}; support "
    297         f"for the old name will be dropped %(removal)s.")
    298     kwargs[new] = kwargs.pop(old)
--> 299 return func(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axes\_base.py:3226, in _AxesBase.grid(self, visible, which, axis, **kwargs)
   3224 _api.check_in_list(['x', 'y', 'both'], axis=axis)
   3225 if axis in ['x', 'both']:
-> 3226     self.xaxis.grid(visible, which=which, **kwargs)
   3227 if axis in ['y', 'both']:
   3228     self.yaxis.grid(visible, which=which, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\_api\deprecation.py:299, in rename_parameter.<locals>.wrapper(*args, **kwargs)
    294     warn_deprecated(
    295         since, message=f"The {old!r} parameter of {func.__name__}() "
    296         f"has been renamed {new!r} since Matplotlib {since}; support "
    297         f"for the old name will be dropped %(removal)s.")
    298     kwargs[new] = kwargs.pop(old)
--> 299 return func(*args, **kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:1434, in Axis.grid(self, visible, which, **kwargs)
   1431 if which in ['major', 'both']:
   1432     gridkw['gridOn'] = (not self._major_tick_kw['gridOn']
   1433                         if visible is None else visible)
-> 1434     self.set_tick_params(which='major', **gridkw)
   1435 self.stale = True

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:873, in Axis.set_tick_params(self, which, reset, **kw)
    871 if which in ['major', 'both']:
    872     self._major_tick_kw.update(kwtrans)
--> 873     for tick in self.majorTicks:
    874         tick._apply_params(**kwtrans)
    875 if which in ['minor', 'both']:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:593, in _LazyTickList.__get__(self, instance, cls)
    591     instance.majorTicks = []
    592     tick = instance._get_tick(major=True)
--> 593     instance.majorTicks.append(tick)
    594     return instance.majorTicks
    595 else:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:592, in _LazyTickList.__get__(self, instance, cls)
    590 if self._major:
    591     instance.majorTicks = []
--> 592     tick = instance._get_tick(major=True)
    593     instance.majorTicks.append(tick)
    594     return instance.majorTicks

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:2057, in XAxis._get_tick(self, major)
   2055 else:
   2056     tick_kw = self._minor_tick_kw
-> 2057 return XTick(self.axes, 0, major=major, **tick_kw)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:415, in XTick.__init__(self, *args, **kwargs)
    414 def __init__(self, *args, **kwargs):
--> 415     super().__init__(*args, **kwargs)
    416     # x in data coords, y in axes coords
    417     ax = self.axes

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\axis.py:172, in Tick.__init__(self, axes, loc, size, width, color, tickdir, pad, labelsize, labelcolor, zorder, gridOn, tick1On, tick2On, label1On, label2On, major, labelrotation, grid_color, grid_linestyle, grid_linewidth, grid_alpha, **kw)
    166 self.gridline.get_path()._interpolation_steps = \
    167     GRIDLINE_INTERPOLATION_STEPS
    168 self.label1 = mtext.Text(
    169     np.nan, np.nan,
    170     fontsize=labelsize, color=labelcolor, visible=label1On,
    171     rotation=self._labelrotation[1])
--> 172 self.label2 = mtext.Text(
    173     np.nan, np.nan,
    174     fontsize=labelsize, color=labelcolor, visible=label2On,
    175     rotation=self._labelrotation[1])
    177 self._apply_tickdir(tickdir)
    179 for artist in [self.tick1line, self.tick2line, self.gridline,
    180                self.label1, self.label2]:

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\text.py:160, in Text.__init__(self, x, y, text, color, verticalalignment, horizontalalignment, multialignment, fontproperties, rotation, linespacing, rotation_mode, usetex, wrap, transform_rotates_text, parse_math, **kwargs)
    158 self._linespacing = linespacing
    159 self.set_rotation_mode(rotation_mode)
--> 160 self.update(kwargs)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\text.py:172, in Text.update(self, kwargs)
    170 # Update bbox last, as it depends on font properties.
    171 bbox = kwargs.pop("bbox", sentinel)
--> 172 super().update(kwargs)
    173 if bbox is not sentinel:
    174     self.set_bbox(bbox)

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\artist.py:1055, in Artist.update(self, props)
   1047 """
   1048 Update this artist's properties from the dict *props*.
   1049 
   (...)
   1052 props : dict
   1053 """
   1054 ret = []
-> 1055 with cbook._setattr_cm(self, eventson=False):
   1056     for k, v in props.items():
   1057         # Allow attributes we want to be able to update through
   1058         # art.update, art.set, setp.
   1059         if k == "axes":

File ~\anaconda3\envs\data_science\lib\contextlib.py:135, in _GeneratorContextManager.__enter__(self)
    133 del self.args, self.kwds, self.func
    134 try:
--> 135     return next(self.gen)
    136 except StopIteration:
    137     raise RuntimeError("generator didn't yield") from None

File ~\anaconda3\envs\data_science\lib\site-packages\matplotlib\cbook\__init__.py:2014, in _setattr_cm(obj, **kwargs)
   2009     left = _unfold(x[1:, :-1:cstride], 0, rstride, rstride)[..., ::-1]
   2010     return (np.concatenate((top, right, bottom, left), axis=2)
   2011               .reshape(-1, 2 * (rstride + cstride)))
-> 2014 @contextlib.contextmanager
   2015 def _setattr_cm(obj, **kwargs):
   2016     """
   2017     Temporarily set some attributes; restore original state at context exit.
   2018     """
   2019     sentinel = object()

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<Figure size 540x720 with 0 Axes>